Computing the confidence levels for a root-mean-square test of goodness-of-fit, II

This paper extends our earlier article, “Computing the confidence levels for a root-mean-square test of goodness-of-fit;” unlike in the earlier article, the models in the present paper involve parameter estimation – both the null and alternative hypotheses in the associated tests are composite. We provide efficient black-box algorithms for calculating the asymptotic confidence levels of a variant on the classic chi-squared test. In some circumstances, it is also feasible to compute the exact confidence levels via Monte Carlo simulation.